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ORCIDJunhong Lin 0003
Person information
- affiliation: Zhejiang University, Center for Data Science, Hangzhou, China
- affiliation: École Polytechnique Fédérale de Lausanne, Laboratory for Information and Inference Systems, Switzerland
Other persons with the same name
- Junhong Lin (aka: Jun-Hong Lin) — disambiguation page
- Junhong Lin 0001
![[0000-0003-3869-1380]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0003-3869-1380")
— Peking University, School of Electronic and Computer Engineering, Shenzhen, China (and 1 more) - Junhong Lin 0002 — Zhejiang University (ZJU), Center for Data Science, Hangzhou, China (and 4 more)
- Junhong Lin 0004 — Massachusetts Institute of Technology, MIT CSAIL, Department of Elctronics Engineering and Computer Science, Cambridge, MA, USA
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2020 – today
- 2026
[j4]Tan Sun, Yusu Hong, Junhong Lin:
Convergence Theory of Sharpness-Aware Minimization With Interpolating Neural Networks. IEEE Trans. Signal Process. 74: 1491-1507 (2026)- 2024
- [i5]Tan Sun, Junhong Lin:
PAC-Bayesian Adversarially Robust Generalization Bounds for Graph Neural Network. CoRR abs/2402.04038 (2024) - 2020
- [j3]Junhong Lin, Volkan Cevher:
Convergences of Regularized Algorithms and Stochastic Gradient Methods with Random Projections. J. Mach. Learn. Res. 21: 20:1-20:44 (2020) - [j2]Junhong Lin, Volkan Cevher:
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral Algorithms. J. Mach. Learn. Res. 21: 147:1-147:63 (2020)
2010 – 2019
- 2019
- [j1]Rabeeh Karimi Mahabadi, Junhong Lin, Volkan Cevher:
A Learning-Based Framework for Quantized Compressed Sensing. IEEE Signal Process. Lett. 26(6): 883-887 (2019) - 2018
- [c2]Junhong Lin, Volkan Cevher:
Optimal Distributed Learning with Multi-pass Stochastic Gradient Methods. ICML 2018: 3098-3107 - [c1]Junhong Lin, Volkan Cevher:
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. ICML 2018: 3108-3117 - [i4]Junhong Lin, Volkan Cevher:
Optimal Rates for Spectral-regularized Algorithms with Least-Squares Regression over Hilbert Spaces. CoRR abs/1801.06720 (2018) - [i3]Junhong Lin, Volkan Cevher:
Optimal Convergence for Distributed Learning with Stochastic Gradient Methods and Spectral-Regularization Algorithms. CoRR abs/1801.07226 (2018) - [i2]Junhong Lin, Volkan Cevher:
Optimal Rates of Sketched-regularized Algorithms for Least-Squares Regression over Hilbert Spaces. CoRR abs/1803.04371 (2018) - [i1]Junhong Lin, Volkan Cevher:
Kernel Conjugate Gradient Methods with Random Projections. CoRR abs/1811.01760 (2018)
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